From Segmentation to Binarization of Gray-Level Images
Maria Frucci, Gabriella Sanniti di Baja
Abstract
For some gray-level images, the boundary between the foreground and the background is perceived in correspondence with the locally maximal changes in gray-level through the image. In this framework, this paper proposes a method to extract the objects of interest from an image and, hence, to distinguish the foreground from the background, starting from a partition of the image obtained by means of watershed transformation. The regions that are assigned to the foreground are also hierarchically ranked, depending on their perceptual relevance, so that different representations of the image are possible.